Emergent Mind

Deterministic Extractors for Additive Sources

(1410.7253)
Published Oct 27, 2014 in cs.CC

Abstract

We propose a new model of a weakly random source that admits randomness extraction. Our model of additive sources includes such natural sources as uniform distributions on arithmetic progressions (APs), generalized arithmetic progressions (GAPs), and Bohr sets, each of which generalizes affine sources. We give an explicit extractor for additive sources with linear min-entropy over both $\mathbb{Z}p$ and $\mathbb{Z}pn$, for large prime $p$, although our results over $\mathbb{Z}pn$ require that the source further satisfy a list-decodability condition. As a corollary, we obtain explicit extractors for APs, GAPs, and Bohr sources with linear min-entropy, although again our results over $\mathbb{Z}pn$ require the list-decodability condition. We further explore special cases of additive sources. We improve previous constructions of line sources (affine sources of dimension 1), requiring a field of size linear in $n$, rather than $\Omega(n2)$ by Gabizon and Raz. This beats the non-explicit bound of $\Theta(n \log n)$ obtained by the probabilistic method. We then generalize this result to APs and GAPs.

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